Last Updated On:  2022-09-26 10:08:55.360157
Author: Philipe Bujold

C:\Anaconda\lib\site-packages\itables\javascript.py:63: UserWarning:

Did you know? init_notebook_mode(all_interactive=False, connected=True) does nothing. Feel free to remove this line, or pass warn_if_call_is_superfluous=False.

C:\Anaconda\lib\site-packages\IPython\core\interactiveshell.py:3457: DtypeWarning:

Columns (5,168,233) have mixed types.Specify dtype option on import or set low_memory=False.

Original dataframe lenght: 4180
...
Lenght after filtering: 4180

Food - Plant-Based Diet #

To understand who people believe might be against talking about these actions.

What we want to be able to say

Are people trying to eat less meat, and what are their motivations for it
Are people talking about eating less meat, sharing it with those they know
Where are the CC possibilities when it comes to meat-reduction interventions

A quick look at our meat-eating behaviors#

C:\Anaconda\lib\site-packages\numpy\core\fromnumeric.py:3208: VisibleDeprecationWarning:

Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.

This first set of questions examined whether respondents are trying to reduce their meat consumption, as well as the beliefs they hold about eating less meat.#

The scores presented in the table represent the weighted average of respondents’ likert responses. Resondents were given a 7-item likert scale for which to answer from Strongly agree to Strongly disagree, the table below showes the weighted average of normalized responses. That is, 1 represents an average responses of Strongly agree, whilst 0 represents an average response of Strongly disagree.

What are some of the steps and reasons to reduce meat consumption given by the respondents?

rename_dict = {col:meta.column_names_to_labels[col] for col in ['pbd_adp_intention', 'pbd_reason_adp', 'pbd_reason_success', 'pbd_adp_why', 'pbd_adp_steps', 'pbd_adp_sharing', 'var427O2785Othr', 'pbd_adp_sharingWhy', 'pbd_social_notSharing_who', 'pbd_adp_roleModel', 'pbd_adp_roleModel_why']}

show(iDTC_enriched[["education", "income", 'age_group', 'SASSY',  'politics', 'state', 'sex','pbd_adp_intention', 'pbd_reason_success', 'pbd_adp_why', 'pbd_adp_steps']].rename(columns=rename_dict).replace('', np.nan).dropna(), column_filters="footer", dom="lrtip", scrollY="300px", scrollCollapse=True, paging=True,  maxBytes=0) #style.background_gradient(subset='age')

	education	income	age_group	SASSY	politics	state	sex	Are you trying to limit your meat consumption?	Has successfully reduced meat eating in the last 5 years	Why are you trying to reduce/limit your meat consumption?	Can you tell us a bit more about the steps you are taking to reduce/limit your meat consumption?
Loading... (need help?)
None	education	income	age_group	SASSY	politics	state	sex	Are you trying to limit your meat consumption?	Has successfully reduced meat eating in the last 5 years	Why are you trying to reduce/limit your meat consumption?	Can you tell us a bit more about the steps you are taking to reduce/limit your meat consumption?

# PBDreasons, _ = survey.gatherScore_fromString(iDTC_enriched.loc[iDTC_enriched['pbd_adp_intention'] == 'Yes'].drop(columns=['pbd_reason_success']), meta, ["pbd_reason"], replaceCols = True)
# PBDreasons.rename(index = {'' : 'How much do you agree or disagree with the following statement?'}, inplace = True)
# display(PBDreasons.T.style.background_gradient(cmap=cm, vmin = 0, vmax = 1))

# PBDreasons, _ = gatherScore_fromString(iDTC_enriched,meta,  ["pbd_attitude"], replaceCols = True)
# # PBDreasons.rename(index = {'pbd_reason' : 'How much do you agree or disagree with the following statement?'}, inplace = True)
# display(PBDreasons.T.style.background_gradient(cmap=cm, vmin = 0, vmax = 1))

Next we look at respondents’ sharing behavior. For those who are intending to eat less meat, are they talking about going meat-free with the people they know?#

Respondents were asked wiith whom the had shared they were trying to eat less meat. The table represents the % respondents who intend to reduce their meat intake and who have shared with X member of their community.

They were also asked whether they thought their community would approve or dissaprove of their decision to reduce meat consumption.

PBDreasons, _ = gatherScore_fromString(iDTC_enriched.loc[iDTC_enriched['pbd_adp_intention'] == 'Yes'], meta, ["pbd_sharing"], replaceCols = True, percentage=True)
# PBDreasons.rename(index = {'pbd_reason' : 'How much do you agree or disagree with the following statement?'}, inplace = True)
display(PBDreasons.T.style.background_gradient(cmap=cm, vmin = 0, vmax = 100))


indexer = [col for col in iDTC_enriched.columns if ("pbd_sharing" in col) |  ("pbd_social" in col)]
_ = survey.plot_single_proportions_2(
    iDTC_enriched[indexer],
    meta,
    title="Social Questions about Meat-Free Diets (those who are intending to reduce)",
    orientation="h",
    showlegend=False,
)

# indexer = [col for col in iDTC_enriched.columns if ("pbd_attitude" in col) ]
# _ = survey.plot_single_proportions_2(
#     iDTC_enriched[indexer],
#     meta,
#     title="Plant-based diet questions",
#     orientation="h",
#     showlegend=False,
# )

	Of the following groups of people in your life, which ones do you think know that you are trying to eat less meat?
Your family	76.392758
Your close friends	54.101835
Your colleagues	14.979179
Your neighbors	12.499653
Your social media followers	10.559358

C:\Anaconda\lib\site-packages\numpy\core\fromnumeric.py:3208: VisibleDeprecationWarning:

Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.

show(iDTC_enriched[["education", "income", 'age_group', 'SASSY',  'politics', 'state', 'sex',  'pbd_adp_intention', 'pbd_reason_success', 'var427O2785Othr', 'pbd_adp_sharingWhy', 'pbd_social_notSharing_who', 'pbd_adp_roleModel', 'pbd_adp_roleModel_why']].replace('',np.nan,regex = True).dropna(how='all', subset=['var427O2785Othr', 'pbd_adp_sharingWhy', 'pbd_social_notSharing_who', 'pbd_adp_roleModel_why']).rename(columns=rename_dict), column_filters="footer", dom="lrtip", scrollY="300px", scrollCollapse=True, paging=True,  maxBytes=0) #style.background_gradient(subset='age')

	education	income	age_group	SASSY	politics	state	sex	Are you trying to limit your meat consumption?	Has successfully reduced meat eating in the last 5 years	Other - Please specify::Of the following groups of people in your life, which ones do you think know that you are trying to eat less meat?	Why have you shared, or why haven't you shared with others?	Please tell us who or which groups of people that would that be?	Who's guidance/tips would you prefer to receive about reducing your meat consumption?	Why would you prefer to receive advice from the group you selected?
Loading... (need help?)
None	education	income	age_group	SASSY	politics	state	sex	Are you trying to limit your meat consumption?	Has successfully reduced meat eating in the last 5 years	Other - Please specify::Of the following groups of people in your life, which ones do you think know that you are trying to eat less meat?	Why have you shared, or why haven't you shared with others?	Please tell us who or which groups of people that would that be?	Who's guidance/tips would you prefer to receive about reducing your meat consumption?	Why would you prefer to receive advice from the group you selected?

Fianlly, we look at some of the potential avenues that ClimateCulture could explore when it comes to meat-reduction interventions#

PBDreasons, _ = gatherScore_fromString(iDTC_enriched,meta,  ["pbd_interest"], replaceCols = True)
# PBDreasons.rename(index = {'pbd_reason' : 'How much do you agree or disagree with the following statement?'}, inplace = True)
display(PBDreasons.T.style.background_gradient(cmap=cm, vmin = 0, vmax = 1))

indexer = [col for col in iDTC_enriched.columns if ("pbd_interest" in col) | ("pbd_adp_roleModel" in col) ]
_ = survey.plot_single_proportions_2(
    iDTC_enriched[indexer],
    meta,
    title="Plant-based diet questions",
    orientation="h",
    showlegend=False,
)

# adp_roleModel

	How much do you agree or disagree with the following statement?
I am interested in learning how reducing my meat consumption can help my health and wellbeing	0.570174
I am interested in learning how reducing my meat consumption can benefit the environment	0.517047
I am interested in learning how reducing my meat consumption can benefit me financially	0.537400
I think positively about organizations that champion healthy food	0.673114
I think positively about organizations that champion environmentally sustainable food	0.628164

# iDTC_enriched.to_excel('all_data_clea.xlsx')

iDTC Sprint Data Analysis

Food - Plant-Based Diet

Contents

Food - Plant-Based Diet #

A quick look at our meat-eating behaviors#

This first set of questions examined whether respondents are trying to reduce their meat consumption, as well as the beliefs they hold about eating less meat.#

Fianlly, we look at some of the potential avenues that ClimateCulture could explore when it comes to meat-reduction interventions#